code: def test_dkwm_mean_two_sample_assertion(self, dtype):
      rng = np.random.RandomState(seed=0)
      num_samples = 4000
  
      # 4000 samples is chosen to be enough to find discrepancies of
      # size 0.2 or more with assurance 1e-6, as confirmed here:
      d = st.min_discrepancy_of_true_means_detectable_by_dkwm_two_sample(
          num_samples,
          0.0,
          1.0,
          num_samples,
          0.0,
          1.0,
          false_fail_rate=1e-6,
          false_pass_rate=1e-6,
      )
      d = self.evaluate(d)
      self.assertLess(d, 0.2)
  
      # Test that the test assertion agrees that the standard
      # uniform distribution has the same mean as itself.
      samples1 = rng.uniform(size=num_samples).astype(dtype=dtype)
      samples2 = rng.uniform(size=num_samples).astype(dtype=dtype)
      self.evaluate(
          st.assert_true_mean_equal_by_dkwm_two_sample(
              samples1,
              0.0,
              1.0,
              samples2,
              0.0,
              1.0,
              false_fail_rate=1e-6,
          )
      )
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 16 for calling the StatisticalTestingTest obj's underlying member method code with example usage: obj.test_dkwm_mean_two_sample_assertion(dtype) without return types